20017908129

Committed 08 Dec 2025 05:36AM UTC coverage: 62.065% (+0.4%) from 61.641%

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zommiommy

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Fix doctests

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44.55

/webgraph/src/utils/mod.rs

/*
 * SPDX-FileCopyrightText: 2023 Inria
 * SPDX-FileCopyrightText: 2023 Sebastiano Vigna
 *
 * SPDX-License-Identifier: Apache-2.0 OR LGPL-2.1-or-later
 */

//! Miscellaneous utilities.

use rand::Rng;
use std::path::PathBuf;

/// Creates a new random dir inside the given folder
pub fn temp_dir<P: AsRef<std::path::Path>>(base: P) -> anyhow::Result<PathBuf> {
    let mut base = base.as_ref().to_owned();
    const ALPHABET: &[u8] = b"0123456789abcdef";
    let mut rnd = rand::rng();
    let mut random_str = String::new();
    loop {
        random_str.clear();
        for _ in 0..16 {
            let idx = rnd.random_range(0..ALPHABET.len());
            random_str.push(ALPHABET[idx] as char);
        }
        base.push(&random_str);

        if !base.exists() {
            std::fs::create_dir(&base)?;
            return Ok(base);
        }
        base.pop();
    }
}

mod batch_codec;
pub use batch_codec::*;

mod circular_buffer;
pub(crate) use circular_buffer::*;

mod mmap_helper;
pub use mmap_helper::*;

mod java_perm;
pub use java_perm::*;

mod granularity;
pub use granularity::*;

pub mod matrix;
pub use matrix::Matrix;

pub mod sort_pairs;
pub use sort_pairs::SortPairs;

pub mod par_sort_pairs;
pub use par_sort_pairs::ParSortPairs;

pub mod par_sort_iters;
pub use par_sort_iters::ParSortIters;

use crate::graphs::{
    arc_list_graph::Iter,
    bvgraph::{Decode, Encode},
};

/// A decoder that encodes the read values using the given encoder.
/// This is commonly used to change the codes of a graph without decoding and
/// re-encoding it but by changing the codes.
pub struct Converter<D: Decode, E: Encode> {
    pub decoder: D,
    pub encoder: E,
    pub offset: usize,
}

impl<D: Decode, E: Encode> Decode for Converter<D, E> {
    // TODO: implement correctly start_node/end_node
    #[inline(always)]
    fn read_outdegree(&mut self) -> u64 {
        let res = self.decoder.read_outdegree();
        self.offset += self.encoder.write_outdegree(res).unwrap();
        res
    }
    #[inline(always)]
    fn read_reference_offset(&mut self) -> u64 {
        let res = self.decoder.read_reference_offset();
        self.offset += self.encoder.write_reference_offset(res).unwrap();
        res
    }
    #[inline(always)]
    fn read_block_count(&mut self) -> u64 {
        let res = self.decoder.read_block_count();
        self.offset += self.encoder.write_block_count(res).unwrap();
        res
    }
    #[inline(always)]
    fn read_block(&mut self) -> u64 {
        let res = self.decoder.read_block();
        self.offset += self.encoder.write_block(res).unwrap();
        res
    }
    #[inline(always)]
    fn read_interval_count(&mut self) -> u64 {
        let res = self.decoder.read_interval_count();
        self.offset += self.encoder.write_interval_count(res).unwrap();
        res
    }
    #[inline(always)]
    fn read_interval_start(&mut self) -> u64 {
        let res = self.decoder.read_interval_start();
        self.offset += self.encoder.write_interval_start(res).unwrap();
        res
    }
    #[inline(always)]
    fn read_interval_len(&mut self) -> u64 {
        let res = self.decoder.read_interval_len();
        self.offset += self.encoder.write_interval_len(res).unwrap();
        res
    }
    #[inline(always)]
    fn read_first_residual(&mut self) -> u64 {
        let res = self.decoder.read_first_residual();
        self.offset += self.encoder.write_first_residual(res).unwrap();
        res
    }
    #[inline(always)]
    fn read_residual(&mut self) -> u64 {
        let res = self.decoder.read_residual();
        self.offset += self.encoder.write_residual(res).unwrap();
        res
    }
    #[inline(always)]
    fn num_of_residuals(&mut self, num_of_residuals: usize) {
        self.encoder.num_of_residuals(num_of_residuals);
    }
}

/// An enum expressing the memory requirements for batched algorithms
/// such as [`SortPairs`], [`ParSortPairs`], and [`ParSortIters`].
///
/// This type implements [`Mul`](core::ops::Mul) and [`Div`](core::ops::Div) to
/// scale the memory usage requirements by a given factor, independently of the
/// variant.
#[derive(Clone, Copy, Debug)]
pub enum MemoryUsage {
    /// The target overall memory usage in bytes.
    ///
    /// This is the more user-friendly option. The actual number of elements
    /// can be computed using [`batch_size`](MemoryUsage::batch_size).
    MemorySize(usize),
    /// The number of elements used in all batches.
    ///
    /// This is a more low-level option that gives more control to the user, but
    /// the actual memory usage will depend on the size of labels (if any).
    BatchSize(usize),
}

/// Default implementation, returning half of the physical RAM.
impl Default for MemoryUsage {
    fn default() -> Self {
        Self::from_perc(50.0)
    }
}

impl core::fmt::Display for MemoryUsage {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        match self {
            MemoryUsage::MemorySize(size) => write!(f, "{} bytes", size),
            MemoryUsage::BatchSize(size) => write!(f, "{} elements", size),
        }
    }
}

impl core::ops::Mul<usize> for MemoryUsage {
    type Output = MemoryUsage;

    fn mul(self, rhs: usize) -> Self::Output {
        match self {
            MemoryUsage::MemorySize(size) => MemoryUsage::MemorySize(size * rhs),
            MemoryUsage::BatchSize(size) => MemoryUsage::BatchSize(size * rhs),
        }
    }
}

impl core::ops::Div<usize> for MemoryUsage {
    type Output = MemoryUsage;

    fn div(self, rhs: usize) -> Self::Output {
        match self {
            MemoryUsage::MemorySize(size) => MemoryUsage::MemorySize(size / rhs),
            MemoryUsage::BatchSize(size) => MemoryUsage::BatchSize(size / rhs),
        }
    }
}

impl MemoryUsage {
    /// Creates a new memory usage expressed as a percentage of the
    /// physical RAM.
    pub fn from_perc(perc: f64) -> Self {
        let system = sysinfo::System::new_with_specifics(
            sysinfo::RefreshKind::nothing()
                .with_memory(sysinfo::MemoryRefreshKind::nothing().with_ram()),
        );
        MemoryUsage::MemorySize(
            usize::try_from((system.total_memory() as f64 * perc / 100.0) as u64)
                .expect("System memory overflows usize"),
        )
    }

    /// Returns the batch size for elements of type `T`.
    ///
    /// If the [memory usage is expressed as a number of
    /// bytes](MemoryUsage::MemorySize), this method divides the number of bytes
    /// by the size of `T` to obtain the number of elements. Otherwise, [it just
    /// returns specified batch size](MemoryUsage::BatchSize).
    pub fn batch_size<T>(&self) -> usize {
        match &self {
            MemoryUsage::MemorySize(memory_size) => {
                let elem_size = std::mem::size_of::<T>();
                assert!(elem_size > 0, "Element size cannot be zero");
                memory_size / elem_size
            }
            MemoryUsage::BatchSize(batch_size) => *batch_size,
        }
    }
}

/// Writes a human-readable representation of a large number using SI prefixes units.
pub fn humanize(value: f64) -> String {
    const UNITS: &[&str] = &["", "K", "M", "G", "T", "P", "E"];
    let mut v = value;
    let mut unit: usize = 0;
    while v >= 1000.0 && unit + 1 < UNITS.len() {
        v /= 1000.0;
        unit += 1;
    }
    if unit == 0 {
        format!("{:.0}{}", v, UNITS[unit])
    } else {
        format!("{:.3}{}", v, UNITS[unit])
    }
}

/// A structure holding partition iterators and their boundaries.
///
/// This type holds a list of iterators and a list of boundaries, one more
/// than the number of iterators. The implied semantics is that each iterator
/// returns (labelled) pairs of nodes, and that the first element of
/// each pair sits between the boundaries associated with the iterator.
///
/// This structures is returned by [`ParSortPairs`] and [`ParSortIters`] and can
/// easily be converted into lenders for use with
/// [`BvCompConfig::par_comp_lenders`](crate::graphs::bvgraph::BvCompConfig::par_comp_lenders)
/// using a convenient implementation of the [`From`] trait.
///
/// Note that it sufficient to write `let lenders: Vec<_> = split_iters.into()`
/// to perform the conversion. Type inference might not work properly if the
/// call is embedded in a larger expression, in which case an explicit type
/// annotation might be necessary.
pub struct SplitIters<I> {
    pub boundaries: Box<[usize]>,
    pub iters: Box<[I]>,
}

impl<I> SplitIters<I> {
    pub fn new(boundaries: Box<[usize]>, iters: Box<[I]>) -> Self {
        Self { boundaries, iters }
    }
}

impl<I> From<(Box<[usize]>, Box<[I]>)> for SplitIters<I> {
    fn from((boundaries, iters): (Box<[usize]>, Box<[I]>)) -> Self {
        Self::new(boundaries, iters)
    }
}

/// Conversion of a [`SplitIters`] of iterators on unlabeled pairs into a
/// sequence of pairs of starting points and associated lenders.
///
/// This is useful for converting the output of sorting utilities like
/// [`ParSortPairs`] or [`ParSortIters`] into a form suitable for
/// [`BvCompConfig::par_comp_lenders`](crate::graphs::bvgraph::BvCompConfig::par_comp_lenders)
/// when working with unlabeled graphs.
///
/// The pairs `(src, dst)` are automatically converted to labeled form with unit
/// labels, and the resulting lenders are wrapped with
/// [`LeftIterator`](crate::labels::proj::LeftIterator) to project out just the
/// successor nodes.
///
/// Note that it sufficient to write `let lenders: Vec<_> = split_iters.into()`
/// to perform the conversion. Type inference might not work properly if the
/// call is embedded in a larger expression, in which case an explicit type
/// annotation might be necessary.
impl<
    I: Iterator<Item = (usize, usize)> + Send + Sync,
    IT: IntoIterator<Item = (usize, usize), IntoIter = I>,
> From<SplitIters<IT>>
    for Vec<
        crate::labels::proj::LeftIterator<
            Iter<(), std::iter::Map<I, fn((usize, usize)) -> ((usize, usize), ())>>,
        >,
    >
{
    fn from(split: SplitIters<IT>) -> Self {
        Box::into_iter(split.iters)
            .enumerate()
            .map(|(i, iter)| {
                let start_node = split.boundaries[i];
                let end_node = split.boundaries[i + 1];
                let num_partition_nodes = end_node - start_node;
                // Map pairs to labeled pairs with unit labels
                #[allow(clippy::type_complexity)]
                let map_fn: fn((usize, usize)) -> ((usize, usize), ()) = |pair| (pair, ());
                let labeled_iter = iter.into_iter().map(map_fn);
                let lender = Iter::try_new_from(num_partition_nodes, labeled_iter, start_node)
                    .expect("Iterator should start from the expected first node");
                // Wrap with LeftIterator to project out just the successor
                crate::labels::proj::LeftIterator(lender)
            })
            .collect()
    }
}

/// Conversion of a [`SplitIters`] of iterators on labelled pairs into a
/// sequences of pairs of starting points and associated lenders.
///
/// This is useful for converting the output of sorting utilities like
/// [`ParSortPairs`] or [`ParSortIters`] into a form suitable for
/// [`BvCompConfig::par_comp_lenders`](crate::graphs::bvgraph::BvCompConfig::par_comp_lenders).
///
/// Note that it sufficient to write `let lenders: Vec<_> = split_iters.into()`
/// to perform the conversion. Type inference might not work properly if the
/// call is embedded in a larger expression, in which case an explicit type
/// annotation might be necessary.
impl<
    L: Clone + Copy + 'static,
    I: Iterator<Item = ((usize, usize), L)> + Send + Sync,
    IT: IntoIterator<Item = ((usize, usize), L), IntoIter = I>,
> From<SplitIters<IT>> for Vec<Iter<L, I>>
{
    fn from(split: SplitIters<IT>) -> Self {
        Box::into_iter(split.iters)
            .enumerate()
            .map(|(i, iter)| {
                let start_node = split.boundaries[i];
                let end_node = split.boundaries[i + 1];
                let num_partition_nodes = end_node - start_node;

                Iter::try_new_from(num_partition_nodes, iter.into_iter(), start_node)
                    .expect("Iterator should start from the expected first node")
            })
            .collect()
    }
}

1	/*
2	* SPDX-FileCopyrightText: 2023 Inria
3	* SPDX-FileCopyrightText: 2023 Sebastiano Vigna
4	*
5	* SPDX-License-Identifier: Apache-2.0 OR LGPL-2.1-or-later
6	*/
7
8	//! Miscellaneous utilities.
9
10	use rand::Rng;
11	use std::path::PathBuf;
12
13	/// Creates a new random dir inside the given folder
14	pub fn temp_dir<P: AsRef<std::path::Path>>(base: P) -> anyhow::Result<PathBuf> {	×
15	let mut base = base.as_ref().to_owned();	×
16	const ALPHABET: &[u8] = b"0123456789abcdef";
17	let mut rnd = rand::rng();	×
18	let mut random_str = String::new();	×
19	loop {	×
20	random_str.clear();	×
21	for _ in 0..16 {	×
22	let idx = rnd.random_range(0..ALPHABET.len());	×
23	random_str.push(ALPHABET[idx] as char);	×
24	}
25	base.push(&random_str);	×
26
27	if !base.exists() {	×
28	std::fs::create_dir(&base)?;	×
29	return Ok(base);	×
30	}
31	base.pop();	×
32	}
33	}
34
35	mod batch_codec;
36	pub use batch_codec::*;
37
38	mod circular_buffer;
39	pub(crate) use circular_buffer::*;
40
41	mod mmap_helper;
42	pub use mmap_helper::*;
43
44	mod java_perm;
45	pub use java_perm::*;
46
47	mod granularity;
48	pub use granularity::*;
49
50	pub mod matrix;
51	pub use matrix::Matrix;
52
53	pub mod sort_pairs;
54	pub use sort_pairs::SortPairs;
55
56	pub mod par_sort_pairs;
57	pub use par_sort_pairs::ParSortPairs;
58
59	pub mod par_sort_iters;
60	pub use par_sort_iters::ParSortIters;
61
62	use crate::graphs::{
63	arc_list_graph::Iter,
64	bvgraph::{Decode, Encode},
65	};
66
67	/// A decoder that encodes the read values using the given encoder.
68	/// This is commonly used to change the codes of a graph without decoding and
69	/// re-encoding it but by changing the codes.
70	pub struct Converter<D: Decode, E: Encode> {
71	pub decoder: D,
72	pub encoder: E,
73	pub offset: usize,
74	}
75
76	impl<D: Decode, E: Encode> Decode for Converter<D, E> {
77	// TODO: implement correctly start_node/end_node
78	#[inline(always)]
79	fn read_outdegree(&mut self) -> u64 {	×
80	let res = self.decoder.read_outdegree();	×
81	self.offset += self.encoder.write_outdegree(res).unwrap();	×
82	res	×
83	}
84	#[inline(always)]
85	fn read_reference_offset(&mut self) -> u64 {	×
86	let res = self.decoder.read_reference_offset();	×
87	self.offset += self.encoder.write_reference_offset(res).unwrap();	×
88	res	×
89	}
90	#[inline(always)]
91	fn read_block_count(&mut self) -> u64 {	×
92	let res = self.decoder.read_block_count();	×
93	self.offset += self.encoder.write_block_count(res).unwrap();	×
94	res	×
95	}
96	#[inline(always)]
97	fn read_block(&mut self) -> u64 {	×
98	let res = self.decoder.read_block();	×
99	self.offset += self.encoder.write_block(res).unwrap();	×
100	res	×
101	}
102	#[inline(always)]
103	fn read_interval_count(&mut self) -> u64 {	×
104	let res = self.decoder.read_interval_count();	×
105	self.offset += self.encoder.write_interval_count(res).unwrap();	×
106	res	×
107	}
108	#[inline(always)]
109	fn read_interval_start(&mut self) -> u64 {	×
110	let res = self.decoder.read_interval_start();	×
111	self.offset += self.encoder.write_interval_start(res).unwrap();	×
112	res	×
113	}
114	#[inline(always)]
115	fn read_interval_len(&mut self) -> u64 {	×
116	let res = self.decoder.read_interval_len();	×
117	self.offset += self.encoder.write_interval_len(res).unwrap();	×
118	res	×
119	}
120	#[inline(always)]
121	fn read_first_residual(&mut self) -> u64 {	×
122	let res = self.decoder.read_first_residual();	×
123	self.offset += self.encoder.write_first_residual(res).unwrap();	×
124	res	×
125	}
126	#[inline(always)]
127	fn read_residual(&mut self) -> u64 {	×
128	let res = self.decoder.read_residual();	×
129	self.offset += self.encoder.write_residual(res).unwrap();	×
130	res	×
131	}
132	#[inline(always)]
133	fn num_of_residuals(&mut self, num_of_residuals: usize) {	×
134	self.encoder.num_of_residuals(num_of_residuals);	×
135	}
136	}
137
138	/// An enum expressing the memory requirements for batched algorithms
139	/// such as [`SortPairs`], [`ParSortPairs`], and [`ParSortIters`].
140	///
141	/// This type implements [`Mul`](core::ops::Mul) and [`Div`](core::ops::Div) to
142	/// scale the memory usage requirements by a given factor, independently of the
143	/// variant.
144	#[derive(Clone, Copy, Debug)]
145	pub enum MemoryUsage {
146	/// The target overall memory usage in bytes.
147	///
148	/// This is the more user-friendly option. The actual number of elements
149	/// can be computed using [`batch_size`](MemoryUsage::batch_size).
150	MemorySize(usize),
151	/// The number of elements used in all batches.
152	///
153	/// This is a more low-level option that gives more control to the user, but
154	/// the actual memory usage will depend on the size of labels (if any).
155	BatchSize(usize),
156	}
157
158	/// Default implementation, returning half of the physical RAM.
159	impl Default for MemoryUsage {
160	fn default() -> Self {	16✔
161	Self::from_perc(50.0)	16✔
162	}
163	}
164
165	impl core::fmt::Display for MemoryUsage {
166	fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {	4✔
167	match self {	4✔
168	MemoryUsage::MemorySize(size) => write!(f, "{} bytes", size),	12✔
169	MemoryUsage::BatchSize(size) => write!(f, "{} elements", size),	×
170	}
171	}
172	}
173
174	impl core::ops::Mul<usize> for MemoryUsage {
175	type Output = MemoryUsage;
176
177	fn mul(self, rhs: usize) -> Self::Output {	×
178	match self {	×
179	MemoryUsage::MemorySize(size) => MemoryUsage::MemorySize(size * rhs),	×
180	MemoryUsage::BatchSize(size) => MemoryUsage::BatchSize(size * rhs),	×
181	}
182	}
183	}
184
185	impl core::ops::Div<usize> for MemoryUsage {
186	type Output = MemoryUsage;
187
188	fn div(self, rhs: usize) -> Self::Output {	16✔
189	match self {	16✔
190	MemoryUsage::MemorySize(size) => MemoryUsage::MemorySize(size / rhs),	32✔
191	MemoryUsage::BatchSize(size) => MemoryUsage::BatchSize(size / rhs),	×
192	}
193	}
194	}
195
196	impl MemoryUsage {
197	/// Creates a new memory usage expressed as a percentage of the
198	/// physical RAM.
199	pub fn from_perc(perc: f64) -> Self {	24✔
200	let system = sysinfo::System::new_with_specifics(
201	sysinfo::RefreshKind::nothing()	24✔
202	.with_memory(sysinfo::MemoryRefreshKind::nothing().with_ram()),	72✔
203	);
204	MemoryUsage::MemorySize(
205	usize::try_from((system.total_memory() as f64 * perc / 100.0) as u64)	72✔
206	.expect("System memory overflows usize"),	24✔
207	)
208	}
209
210	/// Returns the batch size for elements of type `T`.
211	///
212	/// If the [memory usage is expressed as a number of
213	/// bytes](MemoryUsage::MemorySize), this method divides the number of bytes
214	/// by the size of `T` to obtain the number of elements. Otherwise, [it just
215	/// returns specified batch size](MemoryUsage::BatchSize).
216	pub fn batch_size<T>(&self) -> usize {	135✔
217	match &self {	135✔
218	MemoryUsage::MemorySize(memory_size) => {	35✔
219	let elem_size = std::mem::size_of::<T>();	70✔
220	assert!(elem_size > 0, "Element size cannot be zero");	70✔
221	memory_size / elem_size	35✔
222	}
223	MemoryUsage::BatchSize(batch_size) => *batch_size,	200✔
224	}
225	}
226	}
227
228	/// Writes a human-readable representation of a large number using SI prefixes units.
229	pub fn humanize(value: f64) -> String {	128✔
230	const UNITS: &[&str] = &["", "K", "M", "G", "T", "P", "E"];
231	let mut v = value;	256✔
232	let mut unit: usize = 0;	384✔
233	while v >= 1000.0 && unit + 1 < UNITS.len() {	560✔
234	v /= 1000.0;	108✔
235	unit += 1;	108✔
236	}
237	if unit == 0 {	128✔
238	format!("{:.0}{}", v, UNITS[unit])	64✔
239	} else {
240	format!("{:.3}{}", v, UNITS[unit])	192✔
241	}
242	}
243
244	/// A structure holding partition iterators and their boundaries.
245	///
246	/// This type holds a list of iterators and a list of boundaries, one more
247	/// than the number of iterators. The implied semantics is that each iterator
248	/// returns (labelled) pairs of nodes, and that the first element of
249	/// each pair sits between the boundaries associated with the iterator.
250	///
251	/// This structures is returned by [`ParSortPairs`] and [`ParSortIters`] and can
252	/// easily be converted into lenders for use with
253	/// [`BvCompConfig::par_comp_lenders`](crate::graphs::bvgraph::BvCompConfig::par_comp_lenders)
254	/// using a convenient implementation of the [`From`] trait.
255	///
256	/// Note that it sufficient to write `let lenders: Vec<_> = split_iters.into()`
257	/// to perform the conversion. Type inference might not work properly if the
258	/// call is embedded in a larger expression, in which case an explicit type
259	/// annotation might be necessary.
260	pub struct SplitIters<I> {
261	pub boundaries: Box<[usize]>,
262	pub iters: Box<[I]>,
263	}
264
265	impl<I> SplitIters<I> {
266	pub fn new(boundaries: Box<[usize]>, iters: Box<[I]>) -> Self {	2✔
267	Self { boundaries, iters }
268	}
269	}
270
271	impl<I> From<(Box<[usize]>, Box<[I]>)> for SplitIters<I> {
272	fn from((boundaries, iters): (Box<[usize]>, Box<[I]>)) -> Self {	×
273	Self::new(boundaries, iters)	×
274	}
275	}
276
277	/// Conversion of a [`SplitIters`] of iterators on unlabeled pairs into a
278	/// sequence of pairs of starting points and associated lenders.
279	///
280	/// This is useful for converting the output of sorting utilities like
281	/// [`ParSortPairs`] or [`ParSortIters`] into a form suitable for
282	/// [`BvCompConfig::par_comp_lenders`](crate::graphs::bvgraph::BvCompConfig::par_comp_lenders)
283	/// when working with unlabeled graphs.
284	///
285	/// The pairs `(src, dst)` are automatically converted to labeled form with unit
286	/// labels, and the resulting lenders are wrapped with
287	/// [`LeftIterator`](crate::labels::proj::LeftIterator) to project out just the
288	/// successor nodes.
289	///
290	/// Note that it sufficient to write `let lenders: Vec<_> = split_iters.into()`
291	/// to perform the conversion. Type inference might not work properly if the
292	/// call is embedded in a larger expression, in which case an explicit type
293	/// annotation might be necessary.
294	impl<
295	I: Iterator<Item = (usize, usize)> + Send + Sync,
296	IT: IntoIterator<Item = (usize, usize), IntoIter = I>,
297	> From<SplitIters<IT>>
298	for Vec<
299	crate::labels::proj::LeftIterator<
300	Iter<(), std::iter::Map<I, fn((usize, usize)) -> ((usize, usize), ())>>,
301	>,
302	>
303	{
304	fn from(split: SplitIters<IT>) -> Self {	1✔
305	Box::into_iter(split.iters)	2✔
306	.enumerate()
307	.map(\|(i, iter)\| {	5✔
308	let start_node = split.boundaries[i];	8✔
309	let end_node = split.boundaries[i + 1];	8✔
310	let num_partition_nodes = end_node - start_node;	8✔
311	// Map pairs to labeled pairs with unit labels
312	#[allow(clippy::type_complexity)]	×
313	let map_fn: fn((usize, usize)) -> ((usize, usize), ()) = \|pair\| (pair, ());	20✔
314	let labeled_iter = iter.into_iter().map(map_fn);	20✔
315	let lender = Iter::try_new_from(num_partition_nodes, labeled_iter, start_node)	20✔
316	.expect("Iterator should start from the expected first node");	8✔
317	// Wrap with LeftIterator to project out just the successor
318	crate::labels::proj::LeftIterator(lender)	4✔
319	})
320	.collect()
321	}
322	}
323
324	/// Conversion of a [`SplitIters`] of iterators on labelled pairs into a
325	/// sequences of pairs of starting points and associated lenders.
326	///
327	/// This is useful for converting the output of sorting utilities like
328	/// [`ParSortPairs`] or [`ParSortIters`] into a form suitable for
329	/// [`BvCompConfig::par_comp_lenders`](crate::graphs::bvgraph::BvCompConfig::par_comp_lenders).
330	///
331	/// Note that it sufficient to write `let lenders: Vec<_> = split_iters.into()`
332	/// to perform the conversion. Type inference might not work properly if the
333	/// call is embedded in a larger expression, in which case an explicit type
334	/// annotation might be necessary.
335	impl<
336	L: Clone + Copy + 'static,
337	I: Iterator<Item = ((usize, usize), L)> + Send + Sync,
338	IT: IntoIterator<Item = ((usize, usize), L), IntoIter = I>,
339	> From<SplitIters<IT>> for Vec<Iter<L, I>>
340	{
341	fn from(split: SplitIters<IT>) -> Self {	1✔
342	Box::into_iter(split.iters)	2✔
343	.enumerate()
344	.map(\|(i, iter)\| {	4✔
345	let start_node = split.boundaries[i];	6✔
346	let end_node = split.boundaries[i + 1];	6✔
347	let num_partition_nodes = end_node - start_node;	6✔
348
349	Iter::try_new_from(num_partition_nodes, iter.into_iter(), start_node)	15✔
350	.expect("Iterator should start from the expected first node")	6✔
351	})
352	.collect()
353	}
354	}

vigna / webgraph-rs / 20017908129

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